Robust Optimization of ASP Flooding Under Oil Price Uncertainty

Li, Heng; Dang, Cuong Thanh Quy; Mirzabozorg, Arash; Yang, Chaodong; Nghiem, Long X.

doi:10.2118/193837-ms

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…It is important to consider the following aspects, optimized chemical formulation, location of the injector(s), and crude oil price.Thus, the economics of the project depends on the timing of the operation. For example, Li et al 2019 presented the timing of different injection scenarios. Figure 9 shows the timing of ASP injection and the oil price forecast of different designs.…”

Section: The Onset Of Ceor Projectsmentioning

confidence: 99%

Strategy for Optimum Chemical Enhanced Oil Recovery Field Operation

Bigdeli

Delshad

2023

JRR

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IntroductionThe primary source of energy is still fossil fuels which need to be managed properly. Energy consumption is the main motivation behind various hydrocarbon recovery techniques. In general, primary, and secondary techniques of production can result in 20-40% of conventional oil production in place (Nwidee et al. 2016, Thomas 2008, and Muggeridge et al. 2014). As a result, the residual oil will be extracted using various technologies known as Enhanced or Improved Oil Recovery (EOR, or IOR). EOR technologies are classified into three types: thermal, chemical, and gas/solvent injection. Because of the physics of porous media, the trapping and mobilization of crude oil can be difficult to grasp. The underlying physics includes factors, such as high interfacial tension, temperature, oil viscosity, capillary pressure, and complex rock-fluid and fluid-fluid interactions. Injecting chemicals into the reservoir will change the initial equilibrium state of the hydrocarbon fluids, potentially resulting in the mobilization of trapped oil. According to (Machale www.resrecov.com HIGHLIGHTS ➢ A comprehensive review of traditional and novel hybrid CEOR methods. ➢ Provide different methodologies to screen and rank CEOR methods. ➢ Review of experimental workflow for CEOR and scale up methodologies from lab scale to field pilot.

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Section: The Onset Of Ceor Projectsmentioning

confidence: 99%

Strategy for Optimum Chemical Enhanced Oil Recovery Field Operation

Bigdeli

Delshad

2023

JRR

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“…Although they implicitly discussed the impact of uncertain economic parameters, an unknown oil price explicitly affects the NPV in short-term and longterm investigations. In recent years, some studies focused on Utilizing various oil price scenarios to perform RO in Enhanced Oil Recovery (EOR) problems as a technique in reservoir risk management [9,35], by considering the long-term and short-term objectives separately. In addition, another study proposed a robust design for oil production optimization under demand and market uncertainty [20].…”

Section: Introductionmentioning

confidence: 99%

Model-based production optimization under geological and economic uncertainties using multi-objective particle swarm method

Farahi

Ahmadi

Dabir

2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Optimization of the water-flooding process in the oilfields is inherently subject to several uncertainties arising from the imperfect reservoir subsurface model and inadequate data. On the other hand, the uncertainty of economic conditions due to oil price fluctuations puts the decision-making process at risk. It is essential to handle optimization problems under both geological and economic uncertainties. In this study, a Pareto-based Multi-Objective Particle Swarm Optimization (MOPSO) method has been utilized to maximize the short-term and long-term production goals, robust to uncertainties. Some modifications, including applying a variable in the procedure of leader determination, namely crowding distance, a corrected archive controller, and a changing boundary exploration, are performed on the MOPSO algorithm. These corrections led to a complete Pareto front with enough diversity on the investigated model, covering the entire solution space. Net Present Value (NPV) is considered the first goal that represents the long-term gains, while a highly discounted NPV (with a discount rate of 25%) has been considered short-term gains since economic uncertainty risk grows with time. The proposed optimization method has been used to optimize water flooding on the Egg benchmark model. Geological uncertainty is represented with ensembles, including 100 model realizations. The k-means clustering method is utilized to reduce the realizations to 10 to reduce the computing cost. The Pareto front is obtained from Robust Optimization (RO) by maximizing average NPV over the ensembles, as the conservative production plan. Results show that optimization over the ensemble of a reduced number of realizations by the k-means technique is consistent with all realizations’ ensembles results, comparing their cumulative density functions. Furthermore, 10 oil price functions have been considered to form the economic uncertainty space. When SNPV and LNPV are optimized, considering uncertainty in oil price scenarios, the Pareto front’s production scenarios are robust to oil price fluctuations. Using the robust Pareto front of LNPV versus SNPV in both cases, one can optimize production strategy conservatively and update it according to the current reservoir and economic conditions. This approach can help a decision-maker to handle unexpected situations in reservoir management.

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Heavy Oil Reservoir Management - Latest Technologies and Workflows

Aydın

Nagabandi

Temizel

et al. 2022

SPE Western Regional Meeting

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Successful heavy oil reservoir management practices, are built on analyzing and accurately predicting the reservoir behavior over time. To enable these practices, the critical component that assures their success is a thorough understanding of reservoir physics. Given the complex nature of heavy oil reservoirs including geomechanical properties, fluid flow behavior, etc., there is a need to develop a repeatable technique that can account for these complexities within an acceptable margin of accuracy. The objective of this study is to conduct a comprehensive review of all the latest technologies and workflows developed for heavy oil reservoir management, so that, it can be used as a single source of reference for the industry. The latest technologies for heavy oil reservoir management, their underlying principles, along with the advantages and limitations for each of the methods in real-world applications, have been reviewed from different parts of the globe. Based on this review, conclusions have been drawn that help select the best criteria for using the latest heavy oil reservoir management techniques. The primary component of successfully applying heavy oil reservoir management methods, lies in accurately representing the reservoir physics. These components include petrophysical properties, fluid flow and geological properties of a given formation. In addition to outlining each of these components, an emphasis has been given to highlight the important criteria that enable the successful application of these methods to a given area. As such, the study will be an information repository catered to assist in developing robust reservoir management workflows for heavy oil reservoirs. While there are other reference, with examples, on heavy oil reservoir management; the uniqueness of this study lies in summarizing key lessons learned from real-field applications of these methods. Within a single source or reference, this study has given the specific focus on summarizing various aspects that are important to successful heavy oil reservoir management processes.

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Robust Optimization of ASP Flooding Under Oil Price Uncertainty

Cited by 4 publications

References 20 publications

Strategy for Optimum Chemical Enhanced Oil Recovery Field Operation

Strategy for Optimum Chemical Enhanced Oil Recovery Field Operation

Model-based production optimization under geological and economic uncertainties using multi-objective particle swarm method

Heavy Oil Reservoir Management - Latest Technologies and Workflows

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